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How can you tell if a least squares/rootfinding problem is well conditioned only by calculating the roots of a polynomial fit?

QR decomposition help

Overcomplete matrix eigendecomposition

Uniqueness of the QR-factorization

Why is solving linear equation more stable than directly computing matrix inverse?

Sherman-Morrison Formula with Matrices

Why is SVD on $X$ preferred to eigendecomposition of $XX^\top$ in PCA?

Product of positive definite and seminegative definite matrices

Books for Numerical linear algebra

Direct and Iterative methods (GEPP and Jacobi)

Sum of idempotent matrices is Identity

How does Cholupdate work?

Numerical analysis question -- what am I being asked here?

How to solve linear system of form $(A \otimes B + C^{T}C)x = b$ when $A \otimes B$ is too large to compute?

The sum of square of eigenvalues equals minimal Frobenius norm under similar transformation

Advice in Bachelor Degree

New posts in numerical-linear-algebra

Underdetermined Linear Systems and the Least Squares Solution

Approximate a convolution as a sum of separable convolutions

Decompose invertible matrix $A$ as $A = LPU$. (Artin, Chapter 2, Exercise M.11)

Why { $z-x-y=0$ , $z-2x=0$ , $2x+y-3z=0$ } cannot be solved this way?

How can you tell if a least squares/rootfinding problem is well conditioned only by calculating the roots of a polynomial fit?

QR decomposition help

Overcomplete matrix eigendecomposition

Uniqueness of the QR-factorization

Why is solving linear equation more stable than directly computing matrix inverse?

Sherman-Morrison Formula with Matrices

Why is SVD on $X$ preferred to eigendecomposition of $XX^\top$ in PCA?

Product of positive definite and seminegative definite matrices

Books for Numerical linear algebra

Direct and Iterative methods (GEPP and Jacobi)

Sum of idempotent matrices is Identity

How does Cholupdate work?

Numerical analysis question -- what am I being asked here?

How to solve linear system of form $(A \otimes B + C^{T}C)x = b$ when $A \otimes B$ is too large to compute?

The sum of square of eigenvalues equals minimal Frobenius norm under similar transformation

Advice in Bachelor Degree